Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)

Non Local Means Denoising for 3D MR Images

Authors
Hao Song, Jing Jin
Corresponding Author
Hao Song
Available Online March 2013.
DOI
10.2991/iccsee.2013.197How to use a DOI?
Keywords
NL-means, denoising, 3D, MRI, parallelize, GPU
Abstract

Denoising is a crucial step to increase image conspicuity and to improve the performances of all the processing needed for quantitative image analysis. In this paper, the main method we proposed is Non Local Means. We carried out our experiments based on 3D MR images from Brain Web. We compared The NL-means with some classical methods, such as Anisotropic Diffusion Filter and Bilateral Filter. The results show that the Filtering performance of NL-means is better than other methods. Moreover, we present an optimized version of original NL-means and parallelize the computation on GPU device.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
Series
Advances in Intelligent Systems Research
Publication Date
March 2013
ISBN
10.2991/iccsee.2013.197
ISSN
1951-6851
DOI
10.2991/iccsee.2013.197How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Hao Song
AU  - Jing Jin
PY  - 2013/03
DA  - 2013/03
TI  - Non Local Means Denoising for 3D MR Images
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 780
EP  - 783
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.197
DO  - 10.2991/iccsee.2013.197
ID  - Song2013/03
ER  -